predict.hd2part: Prediction method for two part fitted objects

In personalized2part: Two-Part Estimation of Treatment Rules for Semi-Continuous Data

Description

Prediction method for two part fitted objects

Usage

## S3 method for class 'hd2part'
predict(
  object,
  newx,
  s = NULL,
  model = c("zero", "positive"),
  type = c("link", "model_response", "response", "coefficients", "nonzero"),
  newoffset = NULL,
  ...
)

Arguments

object	fitted "hd2part" model object
newx	Matrix of new values for x at which predictions are to be made. Must be a matrix This argument is not used for type=c("coefficients","nonzero")
s	Value(s) of the penalty parameter lambda for the zero part at which predictions are required. Default is the entire sequence used to create the model.
model	either "zero" for the zero part model or "positive" for the positive part model
type	Type of prediction required. type = "link" gives the linear predictors; type = "model_response" gives the fitted probabilities for the zero part and fitted expected values for the positive part. type = "response" gives the combined response prediction across the two models using the full unconditional expected value of the response. When type = "response", argument "model" is unused. type = "coefficients" computes the coefficients at the requested values for s.
newoffset	f an offset is used in the fit, then one must be supplied for making predictions
...	not used

Value

An object depending on the type argument

Examples

set.seed(1)

personalized2part documentation built on Jan. 13, 2021, 7:51 a.m.